Interim Senior ML Engineer

Go Fractional; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

Go Fractional in London is seeking a Senior/Expert ML Engineer to design, train, and optimise personalised recommender systems, while leading data pipelines and production deployment.

The role covers experimentation, cross-functional collaboration, and research into generative AI, with a 12-month fixed-term contract requiring 2 days in the West London office and an end date of 2026-09-30. Proficiency in Python, Scala, TensorFlow, Kubeflow, and PyTorch is expected.

Qualifications

• Experience with ML training frameworks (TFX, Kubeflow) and model serving technologies.
• Proficiency in Python and ML libraries (TensorFlow, PyTorch).
• Experience with large-scale data processing and real-time streaming architectures.
• Strong communication and analytical problem-solving skills.

Responsibilities

• Model Development: design, train, and optimise recommender/personalisation models.
• Data Pipeline Engineering: build scalable pipelines for feature engineering and model training across structured and unstructured data.
• Production Deployment: deploy and monitor ML models in production with high availability.
• Experimentation: design and analyse A/B tests and offline experiments to drive improvement.
• Cross-Functional Collaboration: align ML initiatives with business goals and user needs.
• Research & Innovation: evaluate emerging ML research for integration into systems.

Skills

ML training frameworks

Model serving

Python

TensorFlow

PyTorch

Data streaming

Recommendation systems

Generative AI

Communication

Problem solving

Tools

TensorFlow Serving

Triton

TorchServe

Kubeflow Pipelines SDK

Job description

Who you are

• Strong demonstrated experience using ML Training frameworks (mainly TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance
• Proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch)
• Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving, Triton, TorchServe)
• Experience with high-volume data processing and real-time streaming architectures
• Strong understanding of recommendation system design and personalisation algorithms
• Familiarity with Generative AI and its applications in production settings
• Good communication and analytical problem-solving skills
• If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us!

Desirable

• Experience working on OTT platforms
• Experience in Scala

What the job involves

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance
• Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement
• Cross-Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems

Contract Details

• 12 Month Fixed Term Contract
• Location: London, 2 days a week in office (West London, UK)
• End Date: September 30, 2026
• Level: Senior and Expert level
• Technologies: Python, Scala, TensorFlow, Kubeflow, PyTorch